| CODE | BEM3002 | ||||||||
| TITLE | Statistical Data Analysis in R for Business | ||||||||
| UM LEVEL | 03 - Years 2, 3, 4 in Modular Undergraduate Course | ||||||||
| MQF LEVEL | 6 | ||||||||
| ECTS CREDITS | 4 | ||||||||
| DEPARTMENT | Business and Enterprise Management | ||||||||
| DESCRIPTION | This study-unit focuses on how participants can use the statistical software R to conduct statistical data analysis and to report/communicate the findings. Students will learn the R programming and how to write their own script to carry out statistical data analysis in R. This course provides the basic necessary knowledge for students to understand statistics in R. More specifically, this study-unit will delve into data organisation and exploration procedures, summarising data, graphing data, describing relationships, and mainstream statistical inference techniques generally covered in undergraduate business and management courses. Study-Unit Aims: This study-unit aims to develop the students' capability to conduct statistical analysis of data, to draw conclusions from the data analysis and to communicate these effectively verbally and in writing. Rather than focusing on laborious calculations, the statistical software R will be used as a tool for teaching statistical concepts and to visualise data through the use of the latest developed tools. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit the student will be able to: - Distinguish, choose and apply those statistical methods in common use in marketing, management, business and IT; - Assess the quality of data before proceeding with statistical analysis; - Distinguish and avoid potential mistakes arising from statistical misconceptions; - Operate the resources available for performing statistical analysis in R; - Synthesize and communicate effectively the statistical findings (verbally, visually and in writing). 2. Skills: By the end of the study-unit the student will be able to: - Conduct statistical data analysis and write statistical reports independently; - Evaluate and synthesize statistical reports conducted by others; - Write R script using R programming; - Apply statistical data analysis in R; - Create various charts and figures that are up to standard to the academic world (especially when writing research papers) Main Text/s and any supplementary readings: Main Texts: - Saunders, M., Lewis, P & Thornhill, A. (2012) Research Methods for Business Students (6th edition), Harlow: Pearson. Supplementary Readings: - Monippally, M.M. and Pawar, B.S., 2008. Academic writing: A guide for management students and researchers. SAGE Publications India. - Alvesson, M., & Sandberg, J. (2013). Constructing research questions: Doing interesting research. Sage. |
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| ADDITIONAL NOTES | Pre-requisite Study-unit: EMA1100 | ||||||||
| STUDY-UNIT TYPE | Lecture | ||||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Vincent Marmara |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2024/5. It may be subject to change in subsequent years. |
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